General-purpose agents can plan, use tools, and revise their behavior from feedback, but it remains unclear whether these capabilities transfer from digital environments to embodied manipulation. To investigate this question, we introduce LIBERO-Agent, an agent-native benchmark for evaluating these agents in robot mani...
Zi-Jie Diao, Yi-Tong Chen, Si-Cheng Xie et al.· 3 citations
This work introduces RoboSkill, a framework that connects skill acquisition and reuse through an Explore, Execute, Evolve loop, and complements vision with tactile feedback to reduce uncertainty during physical interaction and augment textual guidance with reusable code to reduce reasoning overhead during skill reuse.
Si-Cheng Xie, Yi-Tong Chen, Hai-Dong Cao et al.· 0 citations
SegDiff, a closed-loop visuomotor policy that decomposes demonstrations into motion segments between keyposes and learns to predict the continuous trajectory from the current state to the next keypose, enabling long-horizon prediction with real-time refinement.
Hai-Dong Cao, Wenjun Cao, Quanhao Li et al.· arXiv.org· 0 citations
FineVLA, an open framework for action-aligned fine-grained VLA supervision, is introduced and the largest real-world gains appear on pose, color, and approach direction, and approach direction--factors where goal-level instructions provide no guidance.
